Numerical Techniques in Finance
Description:
"Numerical Techniques in Finance" is an innovative book that shows how to create, and how to solve problems in a wide variety of complex financial models. All the models are set up using Lotus 1-2-3; some of the advanced models also make use of Lotus macros. Using the models set out in the book, students and practicing professionals will be able to enhance their evaluative and planning skills. Each of the models is preceded by an explanation of the underlying financial theory. Exercises are provided to help the reader utilize the models to create new individualized applications. "Numerical Techniques in Finance" covers standard financial models in the areas of corporate finance, financial statement simulation, portfolio problems, options, portfolio insurance, duration, and immunization. A separate section of the book reviews the relevant mathematical and Lotus 1-2-3 techniques. Each of the book's five parts begins with a succinct overview. Simon Benninga is on the faculty of the School of Business Administration of the Hebrew University. He has been Visiting Professor of Finance at the University of Pennsylvania's Wharton School and at the Graduate School of Management at UCLA.
Best prices to buy, sell, or rent ISBN 9780262022866
Frequently Asked Questions about Numerical Techniques in Finance
You can buy the Numerical Techniques in Finance book at one of 20+ online bookstores with BookScouter, the website that helps find the best deal across the web. Currently, the best offer comes from and is $ for the .
The price for the book starts from $10.54 on Amazon and is available from 3 sellers at the moment.
If you’re interested in selling back the Numerical Techniques in Finance book, you can always look up BookScouter for the best deal. BookScouter checks 30+ buyback vendors with a single search and gives you actual information on buyback pricing instantly.
As for the Numerical Techniques in Finance book, the best buyback offer comes from and is $ for the book in good condition.
Not enough insights yet.
Not enough insights yet.